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Research map / Vision-language and multimodal / Robot action and navigation

ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation

NeurIPS 2023 · Vision-language and multimodal › Robot action and navigation · approach: Memory and subgoal-based manipulation · 10 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add diffusion-based progressive denoising instead of masked image modeling (ablation)ImageBrush · image manipulationprompt fidelity FID (lower better): 78.65 -> 23.97Helped
add diffusion-based progressive denoising instead of masked image modeling (ablation)ImageBrush · image manipulationimage fidelity FID (lower better): 82.33 -> 24.43Helped
add visual prompt cross-attention feature injection (ablation)ImageBrush · image manipulationprompt fidelity FID (lower better): 39.44 -> 23.97Helped
add visual prompt cross-attention feature injection (ablation)ImageBrush · image manipulationimage fidelity FID (lower better): 41.51 -> 24.43Helped
add region-of-interest bounding box input (ablation)ImageBrush · image manipulationprompt fidelity FID (lower better): 24.29 -> 23.97Helped
add region-of-interest bounding box input (ablation)ImageBrush · image manipulationimage fidelity FID (lower better): 25.74 -> 24.43Helped
increase number of in-context examples from 1 to 3 (ablation)ImageBrush · image manipulationprompt and image fidelityHelped
shuffle order of in-context examples (ablation)ImageBrush · image manipulationprompt and image fidelityNo clear effect

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